Matrix spillover remains a challenging issue in flow cytometry analysis, influencing the precision of experimental results. Recently, artificial intelligence (AI) have emerged as promising tools to mitigate matrix spillover effects. AI-mediated approaches leverage sophisticated algorithms to quantify spillover events and adjust for their impact on